Search Results

MicroOptical's Critical Data Viewers are intended to display video images or patient data while mounted in front of the user's eye(s) anytime a video display is used. Typical applications include display of images from endoscopic cameras, ultrasound imaging systems, magnetic resonance imaging systems, or display of data from any type of patient monitor.

MicroOptical's Critical Data Viewers contain an LCD display unit, nonprescription safety glasses, a control box with signal converter and battery mount, cables from viewer to control box and from control box to signal source, a lithium-ion rechargeable battery and a battery charger. The LCD display unit is mounted on a pair of non-prescription safety glasses and is connected via a fourfoot cable to a small battery-powered control box that can be clipped onto a belt. A cable from the control box connects the control box to the video source. The battery is recharged using a separate battery charger. MicroOptical's Critical Data Viewers operate using a standard VGA signal and displaying it onto a small LCD.

The provided text describes MicroOptical's Critical Data Viewers and their 510(k) submission, listing predicate devices and intended use, but it does not contain information about specific acceptance criteria, device performance metrics, or a detailed study proving the device meets acceptance criteria in the way typically found for AI/ML-based medical devices.

The "PERFORMANCE TESTING" section states generally: "MicroOptical's Critical Data Viewers have been subjected to standard optical, electrical, firmware, and mechanical tests to demonstrate the acceptability of the device." This is a very high-level statement and does not provide the granular information requested about acceptance criteria, study design, or specific results.

Therefore, many of the requested fields cannot be populated from the provided document.

Here's a breakdown of what can and cannot be answered based on the text:

1. Table of acceptance criteria and the reported device performance:

• Cannot be provided. The document states "standard optical, electrical, firmware, and mechanical tests" were performed, but no specific acceptance criteria or their corresponding performance results are detailed.

2. Sample sized used for the test set and the data provenance:

• Cannot be provided. No information on specific test sets, sample sizes, or data provenance (country of origin, retrospective/prospective) is given for the "standard tests."

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Cannot be provided. This is not relevant for the type of device (a head-mounted display) or the type of performance testing mentioned (optical, electrical, mechanical). Ground truth establishment by experts is typically for diagnostic/interpretive devices assessing images or data.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Cannot be provided. See point 3.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Cannot be provided. This device is a display system, not an AI/ML diagnostic or assistive tool. There is no mention of such a study.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Cannot be provided. This is not an algorithmic device. Performance would relate to display quality, robustness, etc., not algorithmic output.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Cannot be provided. For "standard optical, electrical, firmware, and mechanical tests," ground truth typically refers to engineering specifications, calibrated measurements, and adherence to established industry standards, not medical ground truth from patient data or expert consensus.

8. The sample size for the training set:

• Cannot be provided. This device does not have a training set in the context of AI/ML.

9. How the ground truth for the training set was established:

• Cannot be provided. See point 8.

In summary: The provided document is a 510(k) summary for a head-mounted display system. Its performance evaluation focuses on engineering and functional capabilities (optical, electrical, mechanical) rather than an AI/ML algorithm's diagnostic accuracy or clinical effectiveness, which would typically involve expert-adjudicated ground truth and specific performance metrics. Therefore, most of the detailed questions regarding study design and AI/ML specific criteria cannot be answered.

Ask a specific question about this device